Papers by Chengxuan Huang

1 papers
Adversarial Math Word Problem Generation (2024.findings-emnlp)

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Challenge: Large language models (LLMs) have revolutionized the educational landscape due to the great improvements in their natural language generation and problem-solving capabilities.
Approach: They propose a cost-effective approach to attack large language models using abstract syntax trees to generate adversarial examples that preserve the structure and difficulty of the original questions aimed for assessment.
Outcome: The proposed approach significantly degrades students' math problem-solving ability on open- and closed-source LLMs.

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